Weather Radar Network Benefit Model for Tornadoes
Weather Radar Network Benefit Model for Tornadoes
复制标题
龙卷风天气雷达网络效益模型
DOI：
10.1175/jamc-d-18-0205.1
复制
发表时间：
2019
影响因子：
3
通讯作者：
J. Kurdzo
中科院分区：
文献类型：
--
作者：
John Y. N. Cho;J. Kurdzo
一个货币化的龙卷风效益模型开发的任意天气雷达网络配置。地理空间回归分析表明，两个关键的雷达参数的垂直空间观测和横向范围的水平分辨率的分数的改善，导致更好的龙卷风预警性能的特点是龙卷风检测概率和误报率。以前的实验结果显示更快的体积扫描速率产生更大的警告性能也纳入模型。增强的龙卷风预警性能反过来又降低了伤亡率。此外，较低的误报率通过减少在避难时损失的工作和个人时间来节省成本。该模型运行在现有的连续的美国天气雷达网络以及假设的未来配置。结果表明，目前的雷达提供了约4.9亿美元（M）yr-1的龙卷风效益。剩余的收益池约为2.6亿美元/年，大致平均分配给覆盖率和快速扫描相关的缺口。
A monetized tornado benefit model is developed for arbitrary weather radar network configurations. Geospatial regression analyses indicate that improvement of two key radar parameters—fraction of vertical space observed and cross-range horizontal resolution—leads to better tornado warning performance as characterized by tornado detection probability and false-alarm ratio. Previous experimental results showing faster volume scan rates yielding greater warning performance are also incorporated into the model. Enhanced tornado warning performance, in turn, reduces casualty rates. In addition, lower false-alarm ratios save costs by cutting down on work and personal time lost while taking shelter. The model is run on the existing contiguous U.S. weather radar network as well as hypothetical future configurations. Results show that the current radars provide a tornado-based benefit of ~$490 million (M) yr−1. The remaining benefit pool is about $260M yr−1, split roughly evenly between coverage- and rapid-scanning-related gaps.